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      Comparative analysis of molecular and morphological diversity in two diploid Paspalum species (Poaceae) with contrasting mating systems.

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          Abstract

          Interspecific comparison of two Paspalum species has demonstrated that mating systems (selfing and outcrossing) contribute to variation (genetically and morphologically) within species through similar but mutually exclusive processes. Mating systems play a key role in the genetic dynamics of populations. Studies show that populations of selfing plants have less genetic diversity than outcrossing plants. Yet, many such studies have ignored morphological diversity. Here, we compared the morphological and molecular diversity patterns in populations of two phylogenetically-related sexual diploids that differ in their mating system: self-sterile Paspalum indecorum and self-fertile P. pumilum. We assessed the morphological variation using 16 morpho-phenological characters and the molecular diversity using three combinations of AFLPs. We compared the morphological and molecular diversity within and among populations in each mating system. Contrary to expectations, selfers showed higher morphological variation within populations, mainly in vegetative and phenological traits, compared to outcrossers. The high morphological variation within populations of selfers led to a low differentiation among populations. At molecular level, selfing populations showed lower levels of genotypic and genetic diversity than outcrossing populations. As expected, selfers showed higher population structure than outcrossers (PhiST = 0.301 and PhiST = 0.108, respectively). Increased homozygous combinations for the same trait/locus enhance morphological variation and reduce molecular variation within populations in selfing P. pumilum. Thus, selfing outcomes are opposite when comparing morphological and molecular variation in P. pumilum. Meanwhile, pollen flow in obligate outcrossing populations of P. indecorum increases within-population molecular variation, but tends to homogenize phenotypes within-population. Pollen flow in obligate outcrossers tends to merge geographically closer populations; but isolation by distance can lead to a weak differentiation among distant populations of P. indecorum.

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          Most cited references83

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          Inference of Population Structure Using Multilocus Genotype Data

          We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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            Detecting the number of clusters of individuals using the software structure: a simulation study

            The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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              STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

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                Author and article information

                Journal
                Plant Reprod
                Plant reproduction
                Springer Science and Business Media LLC
                2194-7961
                2194-7953
                Mar 2024
                : 37
                : 1
                Affiliations
                [1 ] Instituto de Botánica del Nordeste (IBONE-CONICET-UNNE), Facultad de Ciencias Agrarias, Universidad Nacional del Nordeste (FCA-UNNE), 3400, Corrientes, Argentina.
                [2 ] Programa de Estudios Florísticos y Genética Vegetal, Instituto de Biología Subtropical (PEFyGV, IBS-UNaM-CONICET), 3300, Posadas, Argentina.
                [3 ] Department of Systematics, Biodiversity and Evolution of Plants, Albrecht-Von-Haller Institute for Plant Sciences, University of Goettingen, 37073, Goettingen, Germany.
                [4 ] Institute for Population Genetics, Heinrich Heine University, 40225, Düsseldorf, Germany.
                [5 ] Taxonomy and Evolutionary Biology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
                [6 ] Instituto de Botánica del Nordeste (IBONE-CONICET-UNNE), Facultad de Ciencias Agrarias, Universidad Nacional del Nordeste (FCA-UNNE), 3400, Corrientes, Argentina. eric@agr.unne.edu.ar.
                Article
                10.1007/s00497-023-00478-3
                10.1007/s00497-023-00478-3
                37566236
                e3384b8d-79d9-41b8-b72e-ce815f3d9f5e
                History

                Molecular variation,Population structure,Sexuality,Morphological variation,Mating system,Gene flow

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